Udemy - The Complete Intro to Machine Learning with Python

  • CategoryOther
  • TypeTutorials
  • LanguageEnglish
  • Total size2.3 GB
  • Uploaded Byfreecoursewb
  • Downloads97
  • Last checkedOct. 25th '21
  • Date uploadedOct. 22nd '21
  • Seeders 8
  • Leechers11

Infohash : 51A883BB73C428072D3F6602C7ACB5310D44E36F

The Complete Intro to Machine Learning with Python



MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 29 lectures (5h 1m) | Size: 1.89 GB
Hands-on Machine Learning boot-camp with Python, Numpy, Pandas, Regression, Decision Trees, Neural Networks, and more!
What you'll learn:
Learn the basics of data visualization and pre-processing (Python basics, Numpy, Pandas, Seaborn)
Gain theoretical and practical experience with fundamental machine learning algorithms (Linear and Logistic Regression, K-NN, Decision Trees, Neural Networks)
Understand advanced ML topics (encoding, ensemble learning techniques, etc.)
Submit to your first Kaggle Machine Learning Competition

Requirements
No programming or theoretical math prerequisites. We'll teach you everything you need to know.

Description
Interested in machine learning but confused by the jargon? If so, we made this course for you.

Machine learning is the fastest-growing field with constant groundbreaking research. If you're interested in any of the following, you'll be interested in ML:

https://FreeCourseWeb.com

Files:

[ FreeCourseWeb.com ] Udemy - The Complete Intro to Machine Learning with Python
  • Get Bonus Downloads Here.url (0.2 KB)
    • ~Get Your Files Here ! 1. Welcome to the Course
    • 1. Introduction.mp4 (82.8 MB)
    • 1. Introduction.srt (12.7 KB)
    10. Neural Networks
    • 1. Intro to Neural Networks.mp4 (10.6 MB)
    • 1. Intro to Neural Networks.srt (2.0 KB)
    • 2. Origins of Neural Networks.mp4 (25.7 MB)
    • 2. Origins of Neural Networks.srt (4.0 KB)
    • 3. What are neural networks.mp4 (27.0 MB)
    • 3. What are neural networks.srt (4.6 KB)
    • 4. Activation Functions.mp4 (34.8 MB)
    • 4. Activation Functions.srt (5.6 KB)
    • 5. Gradient Descent.mp4 (54.2 MB)
    • 5. Gradient Descent.srt (7.9 KB)
    • 6. Backpropagation.mp4 (89.2 MB)
    • 6. Backpropagation.srt (12.2 KB)
    • 7. Implementation.mp4 (35.9 MB)
    • 7. Implementation.srt (6.2 KB)
    2. Python Review
    • 1. Variable Types.mp4 (75.0 MB)
    • 1. Variable Types.srt (14.1 KB)
    • 2. Lists and Functions.mp4 (73.7 MB)
    • 2. Lists and Functions.srt (15.2 KB)
    • 3. Implementation.mp4 (82.3 MB)
    • 3. Implementation.srt (25.1 KB)
    • 3.1 Python Implementation.ipynb (19.1 KB)
    3. Numpy
    • 1. Numpy Basics.mp4 (59.4 MB)
    • 1. Numpy Basics.srt (11.7 KB)
    • 2. Implementation.mp4 (80.7 MB)
    • 2. Implementation.srt (17.5 KB)
    • 2.1 Numpy Implementation.ipynb (26.5 KB)
    4. Pandas
    • 1. Pandas Basics.mp4 (87.3 MB)
    • 1. Pandas Basics.srt (10.9 KB)
    • 2. Implementation.mp4 (174.3 MB)
    • 2. Implementation.srt (18.1 KB)
    • 2.1 Pandas Implementation.ipynb (25.6 KB)
    5. Seaborn
    • 1. Distribution and Matrix Plots.mp4 (89.3 MB)
    • 1. Distribution and Matrix Plots.srt (19.4 KB)
    • 2. Categorical Plots, Regression Plots, and GridsStyle.mp4 (66.4 MB)
    • 2. Categorical Plots, Regression Plots, and GridsStyle.srt (15.1 KB)
    • 3. Implementation.mp4 (95.6 MB)
    • 3. Implementation.srt (19.3 KB)
    • 3.1 Seaborn Implementation.ipynb (578.7 KB)
    6. Introduction to ML
    • 1. Goals and Types of Machine Learning.mp4 (206.2 MB)
    • 1. Goals and Types of Machine Learning.srt (26.1 KB)
    7. Linear Regression
    • 1. Linear Regression Theory.mp4 (96.7 MB)
    • 1. Linear Regression Theory.srt (16.4 KB)
    • 2. Ordinary Least Squares (OLS).mp4 (89.5 MB)
    • 2. Ordinary Least Squares (OLS).srt (15.5 KB)
    • 3. Implementation Part 1.mp4 (190.5 MB)
    • 3. Implementation Part 1.srt (36.6 KB)
    • 3.1 Linear Regression Implementation.ipynb (136.6 KB)
    • 4. Implementation Part 2.mp4 (50.3 MB)
    • 4. Implementation Part 2.srt (13.3 KB)
    • 4.1 Linear Regression Implementation.ipynb (136.6 KB)
    8. Logistic Regression
    • 1. Logistic Regression Theory.mp4 (132.5 MB)
    • 1. Logistic Regression Theory.srt (15.1 KB)
    • 2. Logistic Regression Metrics and Implementation.mp4 (68.4 MB)
    • 2. Logistic Regression Metrics and Implementation.srt (10.6 KB)
    • 2.1 Logistic Regression Implementation.ipynb (8.5 KB)
    9. Decision Trees
    • 1. Terminology.mp4 (55.4 MB)
    • 1. Terminology.srt (5.8 KB)
    • 2. Splitting Algorithms.mp4 (100.3 MB)
    • 2. Splitting Algorithms.srt (11.0 KB)
    • 3. Random Forests.mp4 (22.1 MB)
    • 3. Random Forests.srt (2.5 KB)
    • 4. Implementation.mp4 (83.8 MB)
    • 4. Implementation.srt (11.4 KB)
    • 4.1 Decision Tree Implementation.ipynb (354.8 KB)
    • Bonus Resources.txt (0.3 KB)

Code:

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